Tag Archives: global illumination

Hi!
Once again, I am going to present you some vulkan features, like pipelines, barriers, memory management, and all things useful for prior ones. This article will be long, but it will be separating into several chapters.

Memory Management

In Vulkan application, it is up to the developer to manage himself the memory. The number of allocations is limited. Make one allocation for one buffer, or one image is really a bad design in Vulkan. One good design is to make a big allocation (let’s call that a chunk), and manage it yourself, and allocate buffer or image within the chunk.

A Chunk Allocator

We need a simple object which has responsibility for allocations of chunks. It just has to select the good heap and call allocate and free from Vulkan API.

Memory Pool

Memory pools are structures used to optimize dynamic allocation performances. In video games, it is not an option to use a memory pool. Ideas are the same I told in the first part. Allocate a chunk, and sub allocate yourself within the chunk. I made a simple generic memory pool.
There is a little scheme which explains what I wanted to do.

Memory Pool

As you can see, video memory is separated into several parts (4 here) and each “Block” in the linked list describes one sub-allocation.
One block is described by :

Size of the block

Offset of the block relatively with the DeviceMemory

A pointer to set data from the host (map)

Boolean to know about the freeness of the block

A sub-allocation within a chunk is performed as follows :

Traverse the linked list until we find a well-sized free block

Modify the size and set the boolean to false

Create a new block, set size, offset and put boolean to true and insert it after the current one.

A free is quite simple, you just have to put the boolean to true.
A good other method could be a “shrink to fit”. If there are some following others with the boolean set to true, we merge all blocks into one.

memorypool.hpp

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#pragma once

#include "chunkallocator.hpp"

// Memory, Offset, Size, ptr

using Allocation=std::tuple<VkDeviceMemory,VkDeviceSize,VkDeviceSize,char*>;

Buffers

Buffers are a well-known part in OpenGL. In Vulkan, it is approximately the same, but you have to manage yourself the memory through one memory pool.

When you create one buffer, you have to give him a size, an usage (uniform buffer, index buffer, vertex buffer, …). You also could ask for a sparse buffer (Sparse resources will be a subject of an article one day ^_^). You also could tell him to be in a mode concurrent. Thanks to that, you could access the same buffer through two different queues.

I chose to have a host visible and host coherent memory. But it is not especially useful. Indeed, to achieve a better performance, you could want to use a non coherent memory (but you will have to flush/invalidate your memory!!).
For the host visible memory, it is not especially useful as well, indeed, for indirect rendering, it could be smart to perform culling with the GPU to fill all structures!

Shaders

Shaders are Different parts of your pipelines. It is an approximation obviously. But, for each part (vertex processing, geometry processing, fragment processing…), shader associated is invoked. In Vulkan, shaders are wrote with SPIR-V.
SPIR-V is “.class” are for Java. You may compile your GLSL sources to SPIR-V using glslangvalidator.

Why is SPIR-V so powerful ?

SPIR-V allows developers to provide their application without the shader’s source.
SPIR-V is an intermediate representation. Thanks to that, vendor implementation does not have to write a specific language compiler. It results in a lower complexity for the driver and it could more optimize, and compile it faster.

Shaders in Vulkan

Contrary to OpenGL’s shader, it is really easy to compile in Vulkan.
My implementation keeps in memory all shaders into a hashtable. It lets to prevent any shader’s recompilation.

Pipelines

Pipelines are objects used for dispatch (compute pipelines) or render something (graphic pipelines).

The beginning of this part is going to be a summarize of the Vulkan’s specs.

Descriptors

Shaders access buffer and image resources through special variables. These variables are organized into a set of bindings. One set is described by one descriptor.

Descriptor Set Layout

They describe one set. One set is compound with an array of bindings. Each bindings are described by :

A binding number

One type : Image, uniform buffer, SSBO, …

The number of values (Could be an array of textures)

Stage where shader could access the binding.

Allocation of Descriptor Sets

They are allocated from descriptor pool objects.
One descriptor pool object is described by a number of set allocation possible, and an array of descriptor type / count it can allocate.

Once you have the descriptor pool, you could allocate from it sets (using both descriptor pool and descriptor set layout).
When you destroy the pool, sets also are destroyed.

Give buffer / image to sets

Now, we have descriptors, but we have to tell Vulkan where shaders can get data from.

Pipeline Layouts

Pipeline layouts are a kind of bridge between the pipeline and descriptor sets. They let you manage push constant as well (we’ll see them in a future article).

Implementation

Since descriptor sets are not coupled with pipelines layout. We could separate pipeline layout and descriptor pool / sets, but currently, I prefer to keep them coupled. It is a choice, and it will maybe change in the future.

Barrier and explanations for the main

I am going to explain quickly what memory barriers are.
The idea behind the memory barrier is ensured writes are performed.
When you performed one compute or one render, it is your duty to ensure that data will be visible when you want to re-use them.

In our main.cpp example, I draw a triangle into a frame buffer and present it.

The first barrier is :

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imageBarrier[0].srcAccessMask=VK_ACCESS_MEMORY_READ_BIT;

imageBarrier[0].dstAccessMask=VK_ACCESS_COLOR_ATTACHMENT_WRITE_BIT;

imageBarrier[0].oldLayout=VK_IMAGE_LAYOUT_PRESENT_SRC_KHR;

imageBarrier[0].newLayout=VK_IMAGE_LAYOUT_COLOR_ATTACHMENT_OPTIMAL;

imageBarrier[0].image=context.surfaceWindow().image(i);

commandPool.commandBarrier(i,

VK_PIPELINE_STAGE_ALL_COMMANDS_BIT,

VK_PIPELINE_STAGE_TOP_OF_PIPE_BIT,

VK_FALSE,memoryBarrier,bufferBarrier,imageBarrier);

Image barriers are compound with access, layout, and pipeline barrier with stage.
Since the presentation is a read of a framebuffer, srcAccessMask is VK_ACCESS_MEMORY_READ_BIT.
Now, we want to render inside this image via a framebuffer, so dstAccessMask is VK_ACCESS_COLOR_ATTACHMENT_WRITE_BIT.

We were presented the image, and now we want to render inside it, so, layouts are obvious.
When we submit image memory barrier to the command buffer, we have to tell it which stages are affected. Here, we wait for all commands and we begin for the first stage of the pipeline.

The second image memory barrier is

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imageBarrier[0].srcAccessMask=VK_ACCESS_COLOR_ATTACHMENT_WRITE_BIT;

imageBarrier[0].dstAccessMask=VK_ACCESS_MEMORY_READ_BIT;

imageBarrier[0].oldLayout=VK_IMAGE_LAYOUT_COLOR_ATTACHMENT_OPTIMAL;

imageBarrier[0].newLayout=VK_IMAGE_LAYOUT_PRESENT_SRC_KHR;

imageBarrier[0].image=context.surfaceWindow().image(i);

commandPool.commandBarrier(i,

VK_PIPELINE_STAGE_COLOR_ATTACHMENT_OUTPUT_BIT,

VK_PIPELINE_STAGE_BOTTOM_OF_PIPE_BIT,

VK_FALSE,memoryBarrier,bufferBarrier,imageBarrier);

The only difference is the order and stageMasks. Here we wait for the color attachement (and not the Fragment one !!!!) and we begin with the end of the stages (It is not really easy to explain… but it does not sound not logic).

It has been a long time since I posted anything on this blog, I am so sorry about it.
I will try to diversify my blog, I’ll talk about C++, Rendering (always <3), and Qt, a framework I love.

So, in this last part, we will talk about photons.

What exactly are Photons ?

A photon is a quantum of light. It carries the light straightforwardly on the medium. Thanks to it, we can see objects etc.

How could we transform photons in a “visible value” like RGB color ?

We saw that the eyes only “see” the radiance !
So we have to transform our photons in radiance.

From physic of photons

We know that one photon have for energy :

where is the wavelength in nm and in Joules.
Say we have photons of each.
We can lay the luminous energy right now :

The luminous flux is just the temporal derivative about the luminous energy :

The idea is great, but we have a luminous flux function of the wavelength, but the radiance is waiting for a general luminous flux
So, we want to have a general flux which is the integral over all wavelengths in the visible spectrum of the luminous flux.

Now, we have the radiance

Using the rendering equation, we get two forms :

The first one take care about dispersion since the second doesn’t.
In this post, I am not going to use the first one, but I could write an article about it latter.

Let’s make our Photon Mapper

What do we need ?

We need a Light which emits photons, so we could add a function “emitPhotons” .